Shift change chaos meets reality: It’s 6:58 a.m. at Station 4. The night crew is still catching up on competing charts from the tail end of their shift. The day crew just walked in, coffee in hand, trying to get the truck checked before the first tone drops. One paramedic is hunting down narc keys, another is on the phone with fleet trying to get a jump-start for the backup unit. Suddenly, the tones chimes and the dispatcher says over the intercom: “Medic 4 respond to an unknown problem/wellness check: priority 2. Third-party caller states the patient hasn’t been seen in 48 hours. Elderly male, history of dementia. No answer at the door. Police enroute to this location.” Your partner flips open the laptop and try to see if there have been other calls to this address and get an understanding of what you may be encountering on scene, only to realize the Wi-Fi is down. You glance at the wall clock. It’s 7:03 a.m. You haven’t completed a truck check, reviewed your crew status or even signed in yet. No one’s slacking. This is just a typical EMS morning, where everything happens at once, and everyone does their best to stay one step ahead of falling behind. | REGISTER: Smart tools, strategic choices: EMS puts AI into action Now imagine a quiet assistant — one that never sleeps — had already: - Verified and corrected the patient’s address using past encounter data - Pulled the previous run report and highlighted key medical history - Populated the ePCR with caller notes, demographics and risk flags - Loaded the relevant dementia/wellness protocol onto your tablet - Logged your crew in, pre-filled the rig checklist, and flagged a low battery in your suction unit This isn’t wishful thinking; it’s exactly what AI